Optimization and characterization of direct coating for ibuprofen particles using a composite fluidized bed

Ibuprofen particles (mean particle size, 27 μm and melting point, 76 °C) as core materials were directly coated with a water-soluble polymer. The primary particles were preserved using a composite fluidized bed with a dispersing mechanism at the bottom of the fluidized bed apparatus. Coated primary particles were obtained under the following 3 conditions: (1) Setting the spray air flow rate at 10 L/min from the initial to 2% coating, (2) adding the low-viscosity water-soluble polymer macrogol 6000 to the hypromellose coating solution, and (3) changing the spray air flow rate to 15 L/min from 2% coating. The particles obtained were confirmed to be coated primary particles by scanning electron microscopy of their cross sections prepared by the cryo-focused ion beam method. The dissolution test showed a marked improvement in the solubility of ibuprofen from the coated primary particles compared with that of a physical mixture. In conclusion, the optimization of the direct coating process made it possible to undertake primary particle coating of a raw material that has a low melting point and a particle size of not more than 50 μm. Primary particle coating contributes to improvements in the physicochemical properties of drugs.     

Target delivery and controlled release of the chemopreventive drug sulindac by using an advanced layered double hydroxide nanomatrix formulation system

Target delivery and controlled release of the chemopreventive drug sulindac that possesses low water solubility present a great challenge for its pharmaceutical industry. Here, we offered an advanced nanomatrix formulation system of sulindac based on layered double hydroxide materials. The X-ray analysis and infrared spectroscopy confirmed the incorporation of sulindac into the gallery of the layered double hydroxides. The incorporation ratios of sulindac were recorded to be 45, 31 and 20 for coprecipitation, anion-exchange and reconstruction techniques, respectively. The scanning electron microscopy showed a nanomatrix-structure of ~50 nm. The release studies of sulindac-nanomatrix showed a 96% controlled release at the small intestine solution during 3 h(s), indicating an enhancement in the dissolution profile of sulindac after the matrix formation. The layered structure of the matrix supplied sulindac with a well-ordered structure and a relatively hydrophobic microenvironment that controlled the guest hydrolysis and reactivity during the release process. The laminar structure of layered double hydroxides offered a safe preservation for sulindac against photodecarboxylation, and enhanced the drug thermal stability from 190 to 230° C. The ionic electrostatic interaction of sulindac through its acidic group with layered double hydroxides demolished the gastrointestinal ulceration.     

A PEG-based biocompatible block catiomer with high buffering capacity for the construction of polyplex micelles showing efficient gene transfer toward primary cells

Nonviral gene vectors from synthetic catiomers (polyplexes) are a promising alternative to viral vectors. In particular, many recent efforts have been devoted to the construction of biocompatible polyplexes for in vivo nonviral gene therapy. A promising approach in this regard is the use of poly(ethylene glycol) (PEG)-based block catiomers, which form a nanoscaled core-shell polyplex with biocompatible PEG palisades. In this study, a series of PEG-based block catiomers with different amine functionalities were newly prepared by a simple and affordable synthetic procedure based on an aminolysis reaction, and their utility as gene carriers was investigated. This study revealed that the block catiomers carrying the ethylenediamine unit at the side chain are capable of efficient and less toxic transfection even toward primary cells, highlighting critical structural factors of the cationic units in the construction of polyplex-type gene vectors. Moreover, the availability of the polyplex micelle for transfection with primary osteoblasts will facilitate its use for bone regeneration in vivo mediated by nonviral gene transfection.     

Voltage fluctuation compensator for Shinkansen

In AC electric railways, three‐phase voltage is changed into the single‐phase circuit of two circuits with the Scott‐connected transformer. If unbalancing of the load between single‐phase circuits becomes large, voltage fluctuation becomes large on the three‐phase side. Railway static power conditioner (RPC) was developed for the purpose of controlling voltage fluctuation on the three‐phase side. An RPC is comprised of a pair of self‐commutated PWM inverters. These inverters connect the main phase and teaser feeding buses, coupled with a DC side capacitor such as a back‐to‐back (BTB) converter. In this way, the two self‐commutated inverters can act as a static var compensator (SVC) to compensate for the reactive power and as an active power accommodator from one feeding bus to another. 20 MVA/60 kV RPCs started commercial operation in 2002 at each two substations on the newly extended Tohoku Shinkansen for compensating voltage fluctuation on the three‐phase side caused by traction loads, absorbing harmonic current. The results of operational testing indicate that an RPC can accommodate single‐phase loads such as those of PWM‐controlled Shinkansen and thyristor phase‐controlled Shinkansen, and handle the exciting rush current of transformers, as well as compensate for harmonics successfully. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 162(4): 25–34, 2007; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20397     

Double enhancement learning for explicit internal representations: unifying self-enhancement and information enhancement to incorporate information on input variables

In this paper, we propose a new type of information-theoretic method called “double enhancement learning,” in which two types of enhancement, namely, self-enhancement and information enhancement, are unified. Self-enhancement learning has been developed to create targets spontaneously within a network, and its performance has proven to be comparable with that of conventional competitive learning and self-organizing maps. To improve the performance of the self-enhancement learning, we try to include information on input variables in the framework of self-enhancement learning. The information on input variables is computed by information enhancement in which a specific input variable is used to enhance competitive unit outputs. This information is again used to train a network with the self-enhancement learning. We applied the method to three problems, namely, an artificial data, a student survey and the voting attitude problem. In all three problems, quantization errors were significantly decreased with the double enhancement learning. The topographic errors were relatively higher, but the smallest number of topographic errors was also obtained by the double enhancement learning. In addition, we saw that U-matrices for all problems showed explicit boundaries reflecting the importance of input variables.     

Stability of bifidobacteria in powdered formula

Two stability tests of bifidobacteria in powdered formula were conducted. In a strain comparison test, three kinds of bifidobacterial powders; Bifidobacterium longum BB536, Bifidobacterium breve M-16V and Bifidobacterium infantis M-63 powders, admixed in follow-up formula were used. In a commercial product evaluation, powdered formulas for toddlers containing bifidobacteria sold in the Indonesian market were analysed. When the inactivation rate constant of each sample, which was used as an index of the loss rate, was determined from the stability tests, B. longum was the most stable strain. The mean inactivation rate constant of commercial products was significantly lower than those obtained in strain comparison, although the same strains ( B. longum BB536 and B. breve M-16V) were used. A possible reason was the lower water activity of commercial products compared to the follow-up formula. Also, higher storage temperature yielded lower stability in all strains or samples, which obeys the Arrhenius theory.     

Controlling Relations between the Individuality and Collectivity of Neurons and its Application to Self-Organizing Maps

In this paper, we consider a society of neurons where different types of neurons interact with each other. For the first approximation to this society, we suppose two types of neurons, namely, individually and collectively treated neurons. Just as individuality must be in harmony with collectivity in actual societies, individually treated neurons must cooperate with collectively treated neurons as much as possible. We here realize this cooperation by making individually treated neurons as similar to collectively treated neurons as possible. The difference between individually and collectively treated neurons is represented by the Kullback–Leibler divergence. This divergence is minimized using free energy minimization. We applied the method to three problems from the well-known machine learning database, namely wine and protein classification, and the image segmentation problem. In all three problems, we succeeded in producing clearer class structures than those obtainable using the conventional SOM. However, we observed that the fidelity to input patterns deteriorated. For this problem, we found that careful treatment of learning processes were needed to keep fidelity to input patterns at an acceptable level.     

Development of fixed-abrasive tool with spiral groove for decreasing the loading

The authors propose a fixed-abrasive tool with spiral groove on its surface, to eliminate or decrease the loading of swarf. The spiral groove, which is produced by a spiral wire wound around the tool, allows continuous evacuation of swarf and elongates the tool life. Through grinding experiments, it was confirmed that our spiral groove tool makes almost no loading of swarf while conventional fixed-abrasive tools easily make it. It was also shown that the spiral groove tool realizes a mirror finish even with ultra fine abrasive grains.     

Enhanced study and control of analyte oxidation in electrospray using a thin-channel,planar electrode emitter

A thin-channel, planar electrode emitter device is described and utilized for the study and control of electrochemical oxidation of analytes at the emitter electrode in an electrospray ion source. For analytes that are not particularly susceptible to oxidation, the planar electrode device functions analytically in a manner similar to emitter systems that utilize the more common stainless steel tubular electrodes. For more easily oxidized analytes, the device provides the means to achieve near 100% oxidation efficiency or to completely eliminate analyte oxidation through simple and rapid changes in electrode material, electrode area, electrode covering, channel height above the electrode, or solution flow rate. Compared to the use of tubular electrodes, the planar electrode emitter system provides improved flexibility in altering the nature of the electrode area and material, as well as altering analyte mass transport to the electrode surface. Each of these parameters is critical in the control of electrochemical reactions and can be easily studied or exploited with this emitter electrode configuration.